Matthew McMullen
Bio
11+ Years Experience in machine learning and AI for collecting and providing the training data sets required for ML and AI development with quality testing and accuracy. Equipped with additional qualification in machine learning.
Stories (30/0)
7 Ways AI is Transforming the Logistics Industry: From Smoother Deliveries to Enhanced Safety
New-age technologies have brought about significant changes in the logistics industry over the past few years. Artificial intelligence (AI), for example, has been a game changer for the supply and demand chains, offering diverse applications like automating repetitive tasks, improving efficiency, and providing better customer experience. Moreover, e-commerce companies can leverage AI for real-time tracking and monitoring of orders.
By Matthew McMullen 26 days ago in Education
Top 8 Large Language Model Enterprise Use Cases
Large language models have drawn significant market attention across industries in a very short span of time. If the upward trend continues, research estimates the generative AI industry could grow at a CAGR of 42% and become a $1.3 trillion market by 2032. Even in its infancy, LLMs already have a multitude of enterprise applications — including content production, translation, transcription, market research, customer support, etc.
By Matthew McMullen 3 months ago in Journal
Polyline Annotation: Boosting the Rise of Automated Vehicles
Welcome to the future, ladies and gentlemen! It is now time for us to sit back, relax, and let our cars handle the driving for us. That's right, autonomous vehicles have arrived, and they are ready for use. We only need to order and our cars will take us from point A to point B. Thanks to artificial intelligence, machine learning, polyline annotation – our cars are ready to take us on a long ride. Whatever the case may be, humans are living in an exciting time. We will no longer have to deal with road rage, parking problems, or annoying backseat drivers instructing us the directions.
By Matthew McMullen 9 months ago in Wheel
Benefit of Sentiment Analysis in the Gaming Industry
There has been a great deal of progress in the gaming industry in recent years. The popularity of video games has grown globally, ranging from simple arcade games to complex virtual worlds. Companies are continually striving to improve their users' gaming experience as the industry continues to evolve. An example of this is the use of sentiment analysis.
By Matthew McMullen 12 months ago in Gamers
Generative AI Models: Steps to Generate a Successful AI Model
Generative AI refers to the creation of artificial systems capable of generating new data or content in the same way that humans do. Images, music, speech, text, and video annotation other types of data can be generated utilizing Generative AI technology.
By Matthew McMullen about a year ago in Journal
AI in Finance 2023 – 5 Benefits for Better Banking
Despite the long-standing technology dependence and the data-intensive nature of the banking sector, data-enabled artificial intelligence (AI) technology can offer a faster and more efficient way to drive ease and efficiency of transacting banking and financial services. Now it is well known that employing AI in finance & banking can contribute to improving productivity, enabling a growth agenda, enhancing differentiation, managing risks and regulatory requirements, and impacting the customer experience positively.
By Matthew McMullen about a year ago in Humans
E-commerce in 2023 — Top 5 Tech Trends that will Reshape the Industry
The E-commerce industry has been at the forefront of the transformation in the era of technology — it has reshaped everything from how customers shop to how the whole e-commerce things operate. Technology has led to significant changes in the e-commerce and retail industries over the past few years. Consumers now have more access to information, are better informed, and are empowered — thanks to the internet, mobile devices, and social media.
By Matthew McMullen about a year ago in Education
How Image Labeling Services Can Empower Computer Vision
There is no comparison between the ability of machine eyes and that of humans to distinguish objects. A machine learning application’s visual perception can be improved by image labeling for machine learning.
By Matthew McMullen about a year ago in Education
Five Ways to Increase Accuracy of Machine Learning Model
Machine Learning (ML) model accuracy is the most important factor that makes such developments successful and reliable in the market. The more accurate the model, it will give the precise results in various scenarios making such a model more meaningful and relevant to enrich the customer experience when used in real life.
By Matthew McMullen about a year ago in Journal
Why Should Your Business Consider Content Moderation?
User-generated content (UGC) is becoming an integral part of the decision-making process for customers when choosing a product or service. Almost half of the consumers think user-generated content is more trustworthy than any other form of media, and even 35% say it is more memorable than any other source.
By Matthew McMullen about a year ago in Journal
Insightful Interpretation of Machine Learning Datasets
It is possible to simulate human intelligence in machines with artificial intelligence (AI) and machine learning (ML). These simulations allow them to complete a variety of tasks without much human assistance - Companies need precise training data if they are to develop AI and ML models that are more efficient and newer. It is possible to gain a better understanding of a given problem through the use of training datasets which can subsequently be enriched through data annotation and labeling for further use as artificial intelligence (AI) training data.
By Matthew McMullen about a year ago in Journal
Training Data to Employ AI in Healthcare
As artificial intelligence (AI) becomes an increasingly important tool in health care, it offers unprecedented opportunities for improving patient outcomes, reducing costs, and impacting population health. There are many examples, including automation, delivering a simple synthesis of complex health information to patients, families, and caregivers, and providing recommendations and visualizations for shared decision-making among patients, family members, and health professionals.
By Matthew McMullen about a year ago in Journal
